ICALEPCS2019 - List of Keywords (booster)

Paper	Title	Other Keywords	Page
MOPHA046	A New Simulation Timing System for Software Testing in Collider-Accelerator Control Systems	timing, controls, simulation, software	307
	Y. Gao, T.G. Robertazzi Stony Brook University, Stony Brook, New York, USA K.A. Brown, M. Harvey, J. Morris, R.H. Olsen BNL, Upton, New York, USA
	Particle accelerators need a timing mechanism to properly accelerate the beam from its source to its destination. The synchronization among accelerator devices is important, which is accomplished by a distribution of timing signals. Devices which require their times synchronized to the acceleration cycle are connected to timelines. Timing signals are sent out along the timelines in the form of digital codes. Correspondingly, devices in the complex are equipped with timeline decoders, which allow devices to extract timing signals appropriately. In this work, a new simulation architecture is introduced which can generate user-specific timing events for software testing in the control systems.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA046
About •	paper received ※ 27 September 2019 paper accepted ※ 08 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUCPL01	Adding Machine Learning to the Analysis and Optimization Toolsets at the Light Source BESSY II	injection, controls, network, operation	754
	L. Vera Ramirez, T. Mertens, R. Müller, J. Viefhaus HZB, Berlin, Germany G. Hartmann University of Kassel, Kassel, Germany
	The Helmholtz Association has initiated the implementation of the Data Management and Analysis concept across its centers in Germany. At Helmholtz-Zentrum Berlin, both the beamline and the machine (accelerator) groups have started working towards setting up the infrastructure and tools to introduce modern analysis, optimization, automation and AI techniques for improving the performance of the (large scale) user facility and its experimental setups. This paper focuses on our first steps with Machine Learning techniques over the past months at BESSY II as well as organizational topics and collaborations. The presented results correspond to two complementary scenarios. The first one is based on supervised ML models trained with real accelerator data, whose target are real-time predictions for several measurements (lifetime, efficiency, beam loss, …); some of these techniques are also used for additional tasks such as outlier detection or feature importance analysis. The second scenario includes first prototypes towards self-tuning of machine parameters in different optimization cases (injection efficiency, orbit correction, …) with Deep Reinforcement Learning agents.
	Slides TUCPL01 [8.894 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-TUCPL01
About •	paper received ※ 27 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPHA089	Design and Implementation of Superconducting Booster Control System	controls, EPICS, interface, cavity	1292
	A.L. Li, Z. Peng, J. Zheng CIAE, Beijing, People’s Republic of China
	In order to improve beam energy, a superconducting booster is built behind the tandem accelerator. The Control system is designed based on EPICS according to its functional needs. It gives a detailed description of hardware and software. The control system realizes data acquisition, network monitoring, Process variable (PV) management, database services, historical data analysis, alarm and other functions of remote device. The running result shows that the control system has fast response time and works stably and reliably, which meets the control requirement.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA089
About •	paper received ※ 30 September 2019 paper accepted ※ 03 October 2020 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

MOPHA046

A New Simulation Timing System for Software Testing in Collider-Accelerator Control Systems

timing, controls, simulation, software

307

Y. Gao, T.G. Robertazzi
Stony Brook University, Stony Brook, New York, USA
K.A. Brown, M. Harvey, J. Morris, R.H. Olsen
BNL, Upton, New York, USA

Particle accelerators need a timing mechanism to properly accelerate the beam from its source to its destination. The synchronization among accelerator devices is important, which is accomplished by a distribution of timing signals. Devices which require their times synchronized to the acceleration cycle are connected to timelines. Timing signals are sent out along the timelines in the form of digital codes. Correspondingly, devices in the complex are equipped with timeline decoders, which allow devices to extract timing signals appropriately. In this work, a new simulation architecture is introduced which can generate user-specific timing events for software testing in the control systems.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA046

About •

paper received ※ 27 September 2019 paper accepted ※ 08 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUCPL01

Adding Machine Learning to the Analysis and Optimization Toolsets at the Light Source BESSY II

injection, controls, network, operation

754

L. Vera Ramirez, T. Mertens, R. Müller, J. Viefhaus
HZB, Berlin, Germany
G. Hartmann
University of Kassel, Kassel, Germany

The Helmholtz Association has initiated the implementation of the Data Management and Analysis concept across its centers in Germany. At Helmholtz-Zentrum Berlin, both the beamline and the machine (accelerator) groups have started working towards setting up the infrastructure and tools to introduce modern analysis, optimization, automation and AI techniques for improving the performance of the (large scale) user facility and its experimental setups. This paper focuses on our first steps with Machine Learning techniques over the past months at BESSY II as well as organizational topics and collaborations. The presented results correspond to two complementary scenarios. The first one is based on supervised ML models trained with real accelerator data, whose target are real-time predictions for several measurements (lifetime, efficiency, beam loss, …); some of these techniques are also used for additional tasks such as outlier detection or feature importance analysis. The second scenario includes first prototypes towards self-tuning of machine parameters in different optimization cases (injection efficiency, orbit correction, …) with Deep Reinforcement Learning agents.

Slides TUCPL01 [8.894 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-TUCPL01

About •

paper received ※ 27 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPHA089

Design and Implementation of Superconducting Booster Control System

controls, EPICS, interface, cavity

1292

A.L. Li, Z. Peng, J. Zheng
CIAE, Beijing, People’s Republic of China

In order to improve beam energy, a superconducting booster is built behind the tandem accelerator. The Control system is designed based on EPICS according to its functional needs. It gives a detailed description of hardware and software. The control system realizes data acquisition, network monitoring, Process variable (PV) management, database services, historical data analysis, alarm and other functions of remote device. The running result shows that the control system has fast response time and works stably and reliably, which meets the control requirement.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA089

About •

paper received ※ 30 September 2019 paper accepted ※ 03 October 2020 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)